System, method, and computer program for adjusting image contrast using parameterized cumulative distribution functions

ABSTRACT

A system and method are provided for optimizing histogram cumulative distribution function curves. In use, a first cumulative distribution function for a first histogram of a first pixel region of a first image is computed, and a first set of parameters for the first cumulative distribution function is extracted. A second cumulative distribution function for a second histogram of a second pixel region of the first image is computed, and a second set of parameters for the second cumulative distribution function is extracted. An interpolated cumulative distribution function comprising interpolated parameters calculated by interpolating between the first set of parameters and the second set of parameters is created. Additionally, a first equalized pixel in a second image based on a first input pixel in the first image and the interpolated cumulative distribution function is generated.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application is a continuation of, and claims priority toU.S. patent application Ser. No. 16/552,649, titled “SYSTEM, METHOD, ANDCOMPUTER PROGRAM FOR ADJUSTING IMAGE CONTRAST USING PARAMETERIZEDCUMULATIVE DISTRIBUTION FUNCTIONS,” filed Aug. 27, 2019, which in turnclaims priority to and the benefit of U.S. patent application Ser. No.16/221,289, titled “SYSTEM, METHOD, AND COMPUTER PROGRAM for ADJUSTINGIMAGE CONTRAST USING PARAMETERIZED CUMULATIVE DISTRIBUTION FUNCTIONS,”filed Dec. 14, 2018, which in turn claims priority to and the benefit ofU.S. Provisional Patent Application No. 62/608,390, titled “SYSTEM,METHOD, AND COMPUTER PROGRAM FOR OPTIMIZING HISTOGRAM CUMULATIVEDISTRIBUTION FUNCTION CURVES,” filed Dec. 20, 2017, all of the foregoingapplications being hereby incorporated by reference for all purposes.

FIELD OF THE INVENTION

The present invention relates to digital image processing, and moreparticularly to adjusting image contrast based on a parameterizedcumulative distribution function.

BACKGROUND

Current digital photographic systems use histogram equalization andadaptive histogram equalization (including contrast-limited techniques)to improve perceived image detail and quality by adjusting contrastwithin digital images. Because adaptive histogram equalization iscomputationally intensive, certain approximation techniques arefrequently implemented to reduce overall computational effort. One suchapproximation involves computing an effective cumulative distributionfunction (CDF) for a given pixel using bilinear interpolation betweenpre-computed CDFs for fixed regions within the image rather thancomputing a unique CDF for a region around the pixel. However, manyissues can arise from using such techniques. For example, bilinearinterpolation can produce visible artifacts along boundaries of thefixed regions in a resulting image. Such artifacts can becomesignificant and degrade image quality when adjacent fixed regions havesufficiently different CDFs.

There is thus a need for addressing these and/or other issues associatedwith the prior art.

SUMMARY

A system and method are provided for optimizing histogram cumulativedistribution function curves. In use, a first cumulative distributionfunction for a first histogram of a first pixel region of a first imageis computed, and a first set of parameters for the first cumulativedistribution function is extracted. A second cumulative distributionfunction for a second histogram of a second pixel region of the firstimage is computed, and a second set of parameters for the secondcumulative distribution function is extracted. An interpolatedcumulative distribution function comprising interpolated parameterscalculated by interpolating between the first set of parameters and thesecond set of parameters is created. Additionally, a first equalizedpixel in a second image based on a first input pixel in the first imageand the interpolated cumulative distribution function is generated.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary method for applying a parameterizedcumulative distribution function to a pixel region, in accordance withone possible embodiment.

FIG. 2A illustrates a method for computing a cumulative distributionfunction, in accordance with one embodiment.

FIG. 2B illustrates a cumulative distribution function and histogram, inaccordance with one embodiment.

FIG. 2C illustrates multiple cumulative distribution functions, inaccordance with one embodiment.

FIG. 2D illustrates a parameterized cumulative distribution function, inaccordance with one embodiment.

FIG. 2E illustrates interpolation based on a cumulative distributionfunction, in accordance with one embodiment.

FIG. 3A illustrates a digital photographic system, in accordance with anembodiment.

FIG. 3B illustrates a processor complex within the digital photographicsystem, according to one embodiment.

FIG. 3C illustrates a digital camera, in accordance with an embodiment.

FIG. 3D illustrates a wireless mobile device, in accordance with anotherembodiment.

FIG. 3E illustrates a camera module configured to sample an image,according to one embodiment.

FIG. 3F illustrates a camera module configured to sample an image,according to another embodiment.

FIG. 3G illustrates a camera module in communication with an applicationprocessor, in accordance with an embodiment.

FIG. 4 illustrates a network service system, in accordance with anotherembodiment.

FIG. 5 illustrates bilinear interpolation artifacts.

FIG. 6 illustrates a network architecture, in accordance with onepossible embodiment.

FIG. 7 illustrates an exemplary system, in accordance with oneembodiment.

DETAILED DESCRIPTION

FIG. 1 illustrates an exemplary method 100 for applying a parameterizedcumulative distribution function to a pixel region, in accordance withone possible embodiment. As shown, a first image is received (seeoperation 102), and the first image is divided into two or more pixelregions (see operation 104). Next, for at least one of the two or morepixel regions, a first histogram is computed (see operation 106), andbased on the first histogram, at least one cumulative distributionfunction for the at least one of the two or more pixel regions iscomputed (see operation 108).

In the context of the present description, a cumulative distributionfunction (“CDF”) comprises a normalized accumulation of histogram valuesfrom a minimum intensity value for the histogram to a maximum intensityvalue for the histogram. In another embodiment, any type of histogramcharacterization function may be used.

Based on the at least one cumulative distribution function, two or morecurve fit coefficients are extracted, (see operation 110). In oneembodiment, the two or more curve fit coefficients (CDF parameters) mayinclude two or more points and two or more corresponding angles. The CDFparameters may be interpolated with respect to a second set of CDFparameters for a second pixel region to create an interpolatedcumulative distribution function (see operation 112). Further, theinterpolated cumulative distribution function is applied to the at leastone of the two or more pixel regions (see operation 114).

In an embodiment, CDF parameters for the first pixel region may be usedto represent a directly computed CDF for first pixel region. In anotherembodiment, a first set of CDF parameters are computed for the firstpixel region and a second set of CDF parameters are computed for thesecond pixel region; furthermore, an interpolated CDF is computed for agiven pixel based on the pixel position within the first pixel region.Any technically feasible technique may be used to interpolate betweenthe first set of CDF parameters and the second set of CDF parameters. Inyet another embodiment, CDF parameters are computed for different pixelregions comprising the first image, and an interpolated CDF for a givenpixel is computed based on the pixel position, with CDF parameters ofsurrounding pixel regions contributing to the interpolated CDF accordingto distance from the pixel.

More illustrative information will now be set forth regarding variousoptional architectures and uses in which the foregoing method may or maynot be implemented, per the desires of the user. It should be stronglynoted that the following information is set forth for illustrativepurposes and should not be construed as limiting in any manner. Any ofthe following features may be optionally incorporated with or withoutthe exclusion of other features described.

FIG. 2A illustrates a method 200 for computing a cumulative distributionfunction, in accordance with one embodiment. As an option, the method200 may be implemented in the context of any one or more of theembodiments set forth in any previous and/or subsequent figure(s) and/ordescription thereof. Of course, however, the method 200 may beimplemented in the context of any desired environment. Further, theaforementioned definitions may equally apply to the description below.

As shown, an image 201A may be divided into two or more pixel regions201B. One specific pixel region 201C may be the basis for which a pixelregion comprising N by N pixels may be determined (as shown in item201D). Next, a histogram 201E is calculated for the pixel region 201C,based on, for example, intensity values of pixels within the pixelregion 201C. Further, a cumulative distribution function 201F may becalculated based on the histogram 201E. The cumulative distributionfunction 201F may be used to equalize a pixel from the center (or anylocation) of pixel region 201C. In one embodiment, the pixel selectedfrom pixel region 201C may be associated with a pre-selected location,and/or may be associated with a pixel of an object in interest. Forexample, a pixel within a pixel region may include an image of a pen,and an object of interest may include a tip of the pen (e.g. based onfocus point, etc.) such that a pixel associated with the tip of the penused to equalize a pixel from the center of the pixel region selected.While the disclosed technique is described with respect to square pixelregions, any shape of region may be implemented without departing thescope of the present disclosure. For example, an N by M (N not equal toM) rectangular pixel region may be used instead of an N by N squarepixel region.

FIG. 2B illustrates a cumulative distribution function and histogram203, in accordance with one embodiment. As an option, the cumulativedistribution function and histogram 203 may be implemented in thecontext of any one or more of the embodiments set forth in any previousand/or subsequent figure(s) and/or description thereof. Of course,however, the cumulative distribution function and histogram 203 may beimplemented in the context of any desired environment. Further, theaforementioned definitions may equally apply to the description below.

As shown, a cumulative distribution function 204 may be generated from ahistogram 202. In one embodiment, the cumulative distribution functionmay include an integral (accumulated sum) of histogram 202, with thearea of the cumulative distribution function 204 normalized, for exampleto one (1.0). Additionally, as has been indicated hereinabove, anotherhistogram characterization function may be used to equalize and/ornormalize the distribution of intensity values of the histogram 202.

FIG. 2C illustrates multiple cumulative distribution functions 205, inaccordance with one embodiment. As an option, the multiple cumulativedistribution functions 205 may be implemented in the context of any oneor more of the embodiments set forth in any previous and/or subsequentfigure(s) and/or description thereof. Of course, however, the multiplecumulative distribution functions 205 may be implemented in the contextof any desired environment. Further, the aforementioned definitions mayequally apply to the description below.

As shown, the multiple cumulative distribution functions 205 may includefunction 206, function 208, function 210, function 212, and/or anynumber of additional functions. Of course, it is to be appreciated thatthe distributions functions 205 may include any number of functions. Byconstruction, cumulative distribution functions may be monotonic (and/orinclude a non-decreasing distribution). In general, cumulativedistribution functions may follow a similar shape (as shown).Consequently, approximating (modeling) a cumulative distributionfunction as a set of curve-fit coefficients of a curve-fit function maybe relatively simple. In one embodiment, any of function 206, function208, function 210, and/or function 212 may be used as the basis fordetermining curve fit coefficients for a parameterized CDF 207 (shownbelow). Further, one or more functions may be created based on histogram202, and of which may be the basis for calculating the determining curvefit coefficients.

FIG. 2D illustrates a parameterized CDF 207, in accordance with oneembodiment. As an option, the a parameterized CDF207 may be implementedin the context of any one or more of the embodiments set forth in anyprevious and/or subsequent figure(s) and/or description thereof. Ofcourse, however, the a parameterized CDF207 may be implemented in thecontext of any desired environment. Further, the aforementioneddefinitions may equally apply to the description below.

As shown, a cumulative distribution function 214 may be modeled as aparameterized CDF by a first point 216A, first angle 218A, second point216B, and second angle 218B. In this context, the first point 216A, thefirst angle 218A, the second point 216B, and the second angle 218Bcomprise control points for an arbitrary spline curve, such a Béziercurve, an exponential function, a NURB, or any other technicallyfeasible parameterized curve element or basis function. Furthermore, anytechnically feasible curve fit basis function may be implemented (e.g.,B-spline, exponential, etc.). Of course, any number of points and anglesmay be used to create a parameterized CDF and/or interpolated CDF. Inone embodiment, an increased number of points and angles may be used fora more accurate parameterized cumulative distribution function, whichmay require an additional computational effort. In an embodiment, at aminimum, two points and angles may be used for purposes of creating aparameterized cumulative distribution function. In this manner, theparameterized CDF may be used to more efficiently represent a CDF for apixel region, as only a small number of control point values need bestored rather than a value for each possible intensity quantizationlevel. Furthermore, interpolating parameters among two or moreparameterized CDF functions can eliminate bilinear filtering artifactsassociated with conventional techniques.

FIG. 2E illustrates interpolation 209 based on a cumulative distributionfunction, in accordance with one embodiment. Such interpolation may beimplemented to approximate individual cumulative distribution functionsfor individual pixels within a given pixel region. As an option, theinterpolation 209 may be implemented in the context of any one or moreof the embodiments set forth in any previous and/or subsequent figure(s)and/or description thereof. Of course, however, the interpolation 209may be implemented in the context of any desired environment. Further,the aforementioned definitions may equally apply to the descriptionbelow.

As shown, the interpolation 209 may be applied to a first image 220 anda first region 222 of first image 220. For a first pixel 224, a pixelregion 225 around the first pixel 224 defines a first vertical distance226 and a second vertical distance 228, as well as a first horizontaldistance 230, and a second horizontal distance 232. Using the firstvertical distance 226, the second vertical distance 228, the firsthorizontal distance 230, and the second horizontal distance 232, acorresponding interpolated CDF may be applied to the pixel 224. In anembodiment, the interpolated CDF is generated by interpolatingrespective parameters for parameterized CDFs of pixel regionssurrounding the first pixel 224; and an equalized pixel value for thefirst pixel 224 is computed using the interpolated parameters in aparameterized CDF generated for the first pixel 224. In anotherembodiment, equalized pixels are generated for the first pixel 224according to parameterized CDFs for surrounding pixel regions the firstpixel 224; and the equalized pixels are interpolated to generate anequalized pixel value for the first pixel 224. Additionally, per FIG.2D, the adjusted cumulative distribution function may be applied to thepixel 224 and to additional pixels comprising the first region 222 offirst image 220.

For example, an interpolation of weights may be applied to the firstregion 222 of first image 220 based on a parameterized and interpolatedCDF (as described herein). A first of multiple interpolations based on aparameterized CDF may be along the horizontal (e.g. such as firsthorizontal distance 230 and second horizontal distance 232).Additionally, a second of the interpolations based on the parameterizedCDF may be along the vertical (e.g. such as first vertical distance 226and second vertical distance 228). A computation for each pixel mayoccur whereby a corresponding interpolated CDF is applied to each pixel.Additionally, an interpolation of weights may be applied to pixelssurrounding such modified pixel within the region 222 of first image 220such that effects of a given parameterized CDF may be propagated to thesurrounding pixels.

In one embodiment, depending on how close the pixel is to a border, agreater weight may be applied (for the interpolation). Additionally, aninterpolation map defining parameter weights for respectiveparameterized CDFs may be constructed and applied, e.g. to the firstpixel 224. Application of an interpolated CDF for each pixel may be usedto equalize (e.g., reassign) an intensity for the first pixel 224. Insuch an embodiment, color and RGB values may be preserved for the firstpixel 224.

In an embodiment, a set of parameterized CDFs for an image may berepresented as an array of CDF parameters. For example, each differentparameterized CDF corresponding to a region of the image may berepresented as array of parameters stored as elements of a texture map.Each of the parameterized CDFs may be represented as curve-fitcoefficients (parameters) for greater storage efficiency relative tostoring a conventional CDF.

It should be noted that although the specification may reference acumulative distribution function (CDF), an interpolated CDF, and/or aparameterized CDF, the techniques disclosed herein may equally apply toany such functions.

Still yet, equalizing a given pixel region may include modifying acontrast over a range of pixels according to pixel position andcorresponding interpolated CDFs. Additionally, the cumulativedistribution function may include a re-mapping for intensity values forpixel. For example, the intensity of pixel values may be adjusted forfirst pixel 224, and/or may be adjusted for pixels surrounding firstpixel 224 within the region 222 of the first image 220 (e.g. based onweights and interpolation). In another embodiment, the intensity ofpixel values may be adjusted for a range of pixels, wherein one pixelfrom each of a plurality of pixel regions is each adjusted.

In another embodiment, the cumulative distribution function may beapplied to a subset of an image. For example, it may be determined thatan object within the image is of high priority (e.g. a face, a building,etc.) and equalization using interpolated CDFs may be applied directlyto the pixel region associated with the high priority object. In oneembodiment, the priority ascribed to a particular object may bepredetermined, and in some instances, provided by user input (e.g., byselecting a point of interest of object type of interest). Additionally,artificial intelligence may be applied to determine one or more parts(or objects) of interest in an image to extract or use as a basis forthe cumulative distribution function.

A pixel region (such as first pixel region 222) may comprise multiplepixels. In another embodiment, a pixel region may be determined based ona selected pixel. In a first step, a histogram is computed for a givenpixel region. As an example, if an image was divided into twenty pixelregions, twenty histograms would be computed. In a second step, acumulative distribution function is computed for each pixel region.Using the same example, for twenty pixel regions, twenty parameterizedCDFs would be computed from respective cumulative distributionfunctions. In contrast to conventional methods and systems, aparameterized cumulative distribution function provides for both a morecompact representation for storage and may inherently eliminate bilinearinterpolation artifacts due to slope matching properties ofparameterized curves including, without limitation, Bézier curves andNURBs.

In one embodiment, an interpolated CDF may include interpolatedcurve-fit coefficients from a two-by-two pixel region of N-by-N pixelseach. An individual interpolated CDF may be applied to equalize anindividual pixel by generating an interpolated CDF at the pixellocation. Alternatively, a pixel may be equalized by four differentcurve-fit cumulative distribution functions, with the resulting fourequalized pixel values interpolated to form a final value for the pixel.Any technically feasible technique may be used to map a pixel value toan equalized pixel value; for example, techniques known in the art maybe applied to perform pixel equalization using the presently disclosedtechnique of generating a curve-fit cumulative distribution function. Inan alternative embodiment, parameterized CDF parameters are interpolatedusing bicubic interpolation.

In one embodiment, use of the adjusted cumulative distribution function(based on the curve fit coefficients) may be used to eliminateartifacts. For example, bilinear interpolation on samples that areover-zoomed may cause artifacts such as subtle horizontal or verticallines (e.g. shown in FIG. 5 ). By using the interpolated CDF, however,such artifacts may be eliminated.

In another embodiment, cumulative distribution functions may differslightly between pixel regions (e.g. shown in FIG. 2C). Notwithstandingsuch differences (which may be very minor), the cumulative distributionfunctions may be represented by approximating such cumulativedistribution functions via at least two points and at least two angles(shown in FIG. 2D). Of course, any number of points and accompanyingangles may be taken. In this manner, rather than recording an entirearray, a number of points and angles may be taken for each cumulativedistribution function.

As such, use of curve fit coefficients to compute a parameterized CDFmay include an ancillary benefit of more efficient processing of dataand less memory, which in turn may require less power and preservebattery usage.

Additionally, use of curve fit coefficients to compute a parameterizedCDF may also eliminate artifacts along bilinear interpolation boundaries(e.g. shown in FIG. 5 ). In this manner, a typical cumulativedistribution function (which may be represented as an array) may bereplaced with adjusted parameterized cumulative distribution function(which may be represented as a function) that can be computed per pixel,per pixel region.

FIG. 3A illustrates a digital photographic system 300, in accordancewith one embodiment. As an option, the digital photographic system 300may be implemented in the context of the details of any of the Figuresdisclosed herein. Of course, however, the digital photographic system300 may be implemented in any desired environment. Further, theaforementioned definitions may equally apply to the description below.

As shown, the digital photographic system 300 may include a processorcomplex 310 coupled to a camera module 330 via an interconnect 334. Inone embodiment, the processor complex 310 is coupled to a strobe unit336. The digital photographic system 300 may also include, withoutlimitation, a display unit 312, a set of input/output devices 314,non-volatile memory 316, volatile memory 318, a wireless unit 340, andsensor devices 342, each coupled to the processor complex 310. In oneembodiment, a power management subsystem 320 is configured to generateappropriate power supply voltages for each electrical load elementwithin the digital photographic system 300. A battery 322 may beconfigured to supply electrical energy to the power management subsystem320. The battery 322 may implement any technically feasible energystorage system, including primary or rechargeable battery technologies.Of course, in other embodiments, additional or fewer features, units,devices, sensors, or subsystems may be included in the system.

In one embodiment, a strobe unit 336 may be integrated into the digitalphotographic system 300 and configured to provide strobe illumination350 during an image sample event performed by the digital photographicsystem 300. In another embodiment, a strobe unit 336 may be implementedas an independent device from the digital photographic system 300 andconfigured to provide strobe illumination 350 during an image sampleevent performed by the digital photographic system 300. The strobe unit336 may comprise one or more LED devices, a gas-discharge illuminator(e.g. a Xenon strobe device, a Xenon flash lamp, etc.), or any othertechnically feasible illumination device. In certain embodiments, two ormore strobe units are configured to synchronously generate strobeillumination in conjunction with sampling an image. In one embodiment,the strobe unit 336 is controlled through a strobe control signal 338 toeither emit the strobe illumination 350 or not emit the strobeillumination 350. The strobe control signal 338 may be implemented usingany technically feasible signal transmission protocol. The strobecontrol signal 338 may indicate a strobe parameter (e.g. strobeintensity, strobe color, strobe time, etc.), for directing the strobeunit 336 to generate a specified intensity and/or color of the strobeillumination 350. The strobe control signal 338 may be generated by theprocessor complex 310, the camera module 330, or by any othertechnically feasible combination thereof. In one embodiment, the strobecontrol signal 338 is generated by a camera interface unit within theprocessor complex 310 and transmitted to both the strobe unit 336 andthe camera module 330 via the interconnect 334. In another embodiment,the strobe control signal 338 is generated by the camera module 330 andtransmitted to the strobe unit 336 via the interconnect 334.

Optical scene information 352, which may include at least a portion ofthe strobe illumination 350 reflected from objects in the photographicscene, is focused as an optical image onto an image sensor 332 withinthe camera module 330. The image sensor 332 generates an electronicrepresentation of the optical image. The electronic representationcomprises spatial color intensity information, which may includedifferent color intensity samples (e.g. red, green, and blue light,etc.). In other embodiments, the spatial color intensity information mayalso include samples for white light. The electronic representation istransmitted to the processor complex 310 via the interconnect 334, whichmay implement any technically feasible signal transmission protocol.

In one embodiment, input/output devices 314 may include, withoutlimitation, a capacitive touch input surface, a resistive tablet inputsurface, one or more buttons, one or more knobs, light-emitting devices,light detecting devices, sound emitting devices, sound detectingdevices, or any other technically feasible device for receiving userinput and converting the input to electrical signals, or convertingelectrical signals into a physical signal. In one embodiment, theinput/output devices 314 include a capacitive touch input surfacecoupled to a display unit 312. A touch entry display system may includethe display unit 312 and a capacitive touch input surface, also coupledto processor complex 310.

Additionally, in other embodiments, non-volatile (NV) memory 316 isconfigured to store data when power is interrupted. In one embodiment,the NV memory 316 comprises one or more flash memory devices (e.g. ROM,PCM, FeRAM, FRAM, PRAM, MRAM, NRAM, etc.). The NV memory 316 comprises anon-transitory computer-readable medium, which may be configured toinclude programming instructions for execution by one or more processingunits within the processor complex 310. The programming instructions mayimplement, without limitation, an operating system (OS), UI softwaremodules, image processing and storage software modules, one or moreinput/output devices 314 connected to the processor complex 310, one ormore software modules for sampling an image stack through camera module330, one or more software modules for presenting the image stack or oneor more synthetic images generated from the image stack through thedisplay unit 312. As an example, in one embodiment, the programminginstructions may also implement one or more software modules for mergingimages or portions of images within the image stack, aligning at leastportions of each image within the image stack, or a combination thereof.In another embodiment, the processor complex 310 may be configured toexecute the programming instructions, which may implement one or moresoftware modules operable to create a high dynamic range (HDR) image.

Still yet, in one embodiment, one or more memory devices comprising theNV memory 316 may be packaged as a module configured to be installed orremoved by a user. In one embodiment, volatile memory 318 comprisesdynamic random access memory (DRAM) configured to temporarily storeprogramming instructions, image data such as data associated with animage stack, and the like, accessed during the course of normaloperation of the digital photographic system 300. Of course, thevolatile memory may be used in any manner and in association with anyother input/output device 314 or sensor device 342 attached to theprocess complex 310.

In one embodiment, sensor devices 342 may include, without limitation,one or more of an accelerometer to detect motion and/or orientation, anelectronic gyroscope to detect motion and/or orientation, a magneticflux detector to detect orientation, a global positioning system (GPS)module to detect geographic position, or any combination thereof. Ofcourse, other sensors, including but not limited to a motion detectionsensor, a proximity sensor, an RGB light sensor, a gesture sensor, a 3-Dinput image sensor, a pressure sensor, and an indoor position sensor,may be integrated as sensor devices. In one embodiment, the sensordevices may be one example of input/output devices 314.

Wireless unit 340 may include one or more digital radios configured tosend and receive digital data. In particular, the wireless unit 340 mayimplement wireless standards (e.g. WiFi, Bluetooth, NFC, etc.), and mayimplement digital cellular telephony standards for data communication(e.g. CDMA, 3G, 4G, LTE, LTE-Advanced, etc.). Of course, any wirelessstandard or digital cellular telephony standards may be used.

In one embodiment, the digital photographic system 300 is configured totransmit one or more digital photographs to a network-based (online) or“cloud-based” photographic media service via the wireless unit 340. Theone or more digital photographs may reside within either the NV memory316 or the volatile memory 318, or any other memory device associatedwith the processor complex 310. In one embodiment, a user may possesscredentials to access an online photographic media service and totransmit one or more digital photographs for storage to, retrieval from,and presentation by the online photographic media service. Thecredentials may be stored or generated within the digital photographicsystem 300 prior to transmission of the digital photographs. The onlinephotographic media service may comprise a social networking service,photograph sharing service, or any other network-based service thatprovides storage of digital photographs, processing of digitalphotographs, transmission of digital photographs, sharing of digitalphotographs, or any combination thereof. In certain embodiments, one ormore digital photographs are generated by the online photographic mediaservice based on image data (e.g. image stack, HDR image stack, imagepackage, etc.) transmitted to servers associated with the onlinephotographic media service. In such embodiments, a user may upload oneor more source images from the digital photographic system 300 forprocessing by the online photographic media service.

In one embodiment, the digital photographic system 300 comprises atleast one instance of a camera module 330. In another embodiment, thedigital photographic system 300 comprises a plurality of camera modules330. Such an embodiment may also include at least one strobe unit 336configured to illuminate a photographic scene, sampled as multiple viewsby the plurality of camera modules 330. The plurality of camera modules330 may be configured to sample a wide angle view (e.g., greater thanforty-five degrees of sweep among cameras) to generate a panoramicphotograph. In one embodiment, a plurality of camera modules 330 may beconfigured to sample two or more narrow angle views (e.g., less thanforty-five degrees of sweep among cameras) to generate a stereoscopicphotograph. In other embodiments, a plurality of camera modules 330 maybe configured to generate a 3-D image or to otherwise display a depthperspective (e.g. a z-component, etc.) as shown on the display unit 312or any other display device.

In one embodiment, a display unit 312 may be configured to display atwo-dimensional array of pixels to form an image for display. Thedisplay unit 312 may comprise a liquid-crystal (LCD) display, alight-emitting diode (LED) display, an organic LED display, or any othertechnically feasible type of display. In certain embodiments, thedisplay unit 312 may be able to display a narrower dynamic range ofimage intensity values than a complete range of intensity values sampledfrom a photographic scene, such as within a single HDR image or over aset of two or more images comprising a multiple exposure or HDR imagestack. In one embodiment, images comprising an image stack may be mergedaccording to any technically feasible HDR blending technique to generatea synthetic image for display within dynamic range constraints of thedisplay unit 312. In one embodiment, the limited dynamic range mayspecify an eight-bit per color channel binary representation ofcorresponding color intensities. In other embodiments, the limiteddynamic range may specify more than eight-bits (e.g., 10 bits, 12 bits,or 14 bits, etc.) per color channel binary representation.

FIG. 3B illustrates a processor complex 310 within the digitalphotographic system 300 of FIG. 3A, in accordance with one embodiment.As an option, the processor complex 310 may be implemented in thecontext of the details of any of the Figures disclosed herein. Ofcourse, however, the processor complex 310 may be implemented in anydesired environment. Further, the aforementioned definitions may equallyapply to the description below.

As shown, the processor complex 310 includes a processor subsystem 360and may include a memory subsystem 362. In one embodiment, processorcomplex 310 may comprise a system on a chip (SoC) device that implementsprocessor subsystem 360, and memory subsystem 362 comprises one or moreDRAM devices coupled to the processor subsystem 360. In anotherembodiment, the processor complex 310 may comprise a multi-chip module(MCM) encapsulating the SoC device and the one or more DRAM devicescomprising the memory subsystem 362.

The processor subsystem 360 may include, without limitation, one or morecentral processing unit (CPU) cores 370, a memory interface 380,input/output interfaces unit 384, and a display interface unit 382, eachcoupled to an interconnect 374. The one or more CPU cores 370 may beconfigured to execute instructions residing within the memory subsystem362, volatile memory 318, NV memory 316, or any combination thereof.Each of the one or more CPU cores 370 may be configured to retrieve andstore data through interconnect 374 and the memory interface 380. In oneembodiment, each of the one or more CPU cores 370 may include a datacache, and an instruction cache. Additionally, two or more of the CPUcores 370 may share a data cache, an instruction cache, or anycombination thereof. In one embodiment, a cache hierarchy is implementedto provide each CPU core 370 with a private cache layer, and a sharedcache layer.

In some embodiments, processor subsystem 360 may include one or moregraphics processing unit (GPU) cores 372. Each GPU core 372 may comprisea plurality of multi-threaded execution units that may be programmed toimplement, without limitation, graphics acceleration functions. Invarious embodiments, the GPU cores 372 may be configured to executemultiple thread programs according to well-known standards (e.g.OpenGL™, WebGL™, OpenCL™, CUDA™, etc.), and/or any other programmablerendering graphic standard. In certain embodiments, at least one GPUcore 372 implements at least a portion of a motion estimation function,such as a well-known Harris detector or a well-known Hessian-Laplacedetector. Such a motion estimation function may be used at least in partto align images or portions of images within an image stack. Forexample, in one embodiment, an HDR image may be compiled based on animage stack, where two or more images are first aligned prior tocompiling the HDR image.

As shown, the interconnect 374 is configured to transmit data betweenand among the memory interface 380, the display interface unit 382, theinput/output interfaces unit 384, the CPU cores 370, and the GPU cores372. In various embodiments, the interconnect 374 may implement one ormore buses, one or more rings, a cross-bar, a mesh, or any othertechnically feasible data transmission structure or technique. Thememory interface 380 is configured to couple the memory subsystem 362 tothe interconnect 374. The memory interface 380 may also couple NV memory316, volatile memory 318, or any combination thereof to the interconnect374. The display interface unit 382 may be configured to couple adisplay unit 312 to the interconnect 374. The display interface unit 382may implement certain frame buffer functions (e.g. frame refresh, etc.).Alternatively, in another embodiment, the display unit 312 may implementcertain frame buffer functions (e.g. frame refresh, etc.). Theinput/output interfaces unit 384 may be configured to couple variousinput/output devices to the interconnect 374.

In certain embodiments, a camera module 330 is configured to storeexposure parameters for sampling each image associated with an imagestack. For example, in one embodiment, when directed to sample aphotographic scene, the camera module 330 may sample a set of imagescomprising the image stack according to stored exposure parameters. Asoftware module comprising programming instructions executing within aprocessor complex 310 may generate and store the exposure parametersprior to directing the camera module 330 to sample the image stack. Inother embodiments, the camera module 330 may be used to meter an imageor an image stack, and the software module comprising programminginstructions executing within a processor complex 310 may generate andstore metering parameters prior to directing the camera module 330 tocapture the image. Of course, the camera module 330 may be used in anymanner in combination with the processor complex 310.

In one embodiment, exposure parameters associated with images comprisingthe image stack may be stored within an exposure parameter datastructure that includes exposure parameters for one or more images. Inanother embodiment, a camera interface unit (not shown in FIG. 3B)within the processor complex 310 may be configured to read exposureparameters from the exposure parameter data structure and to transmitassociated exposure parameters to the camera module 330 in preparationof sampling a photographic scene. After the camera module 330 isconfigured according to the exposure parameters, the camera interfacemay direct the camera module 330 to sample the photographic scene; thecamera module 330 may then generate a corresponding image stack. Theexposure parameter data structure may be stored within the camerainterface unit, a memory circuit within the processor complex 310,volatile memory 318, NV memory 316, the camera module 330, or within anyother technically feasible memory circuit. Further, in anotherembodiment, a software module executing within processor complex 310 maygenerate and store the exposure parameter data structure.

FIG. 3C illustrates a digital camera 302, in accordance with oneembodiment. As an option, the digital camera 302 may be implemented inthe context of the details of any of the Figures disclosed herein. Ofcourse, however, the digital camera 302 may be implemented in anydesired environment. Further, the aforementioned definitions may equallyapply to the description below.

In one embodiment, the digital camera 302 may be configured to include adigital photographic system, such as digital photographic system 300 ofFIG. 3A. As shown, the digital camera 302 includes a camera module 330,which may include optical elements configured to focus optical sceneinformation representing a photographic scene onto an image sensor,which may be configured to convert the optical scene information to anelectronic representation of the photographic scene.

Additionally, the digital camera 302 may include a strobe unit 336, andmay include a shutter release button 315 for triggering a photographicsample event, whereby digital camera 302 samples one or more imagescomprising the electronic representation. In other embodiments, anyother technically feasible shutter release mechanism may trigger thephotographic sample event (e.g. such as a timer trigger or remotecontrol trigger, etc.).

FIG. 3D illustrates a wireless mobile device 376, in accordance with oneembodiment. As an option, the mobile device 376 may be implemented inthe context of the details of any of the Figures disclosed herein. Ofcourse, however, the mobile device 376 may be implemented in any desiredenvironment. Further, the aforementioned definitions may equally applyto the description below.

In one embodiment, the mobile device 376 may be configured to include adigital photographic system (e.g. such as digital photographic system300 of FIG. 3A), which is configured to sample a photographic scene. Invarious embodiments, a camera module 330 may include optical elementsconfigured to focus optical scene information representing thephotographic scene onto an image sensor, which may be configured toconvert the optical scene information to an electronic representation ofthe photographic scene. Further, a shutter release command may begenerated through any technically feasible mechanism, such as a virtualbutton, which may be activated by a touch gesture on a touch entrydisplay system comprising display unit 312, or a physical button, whichmay be located on any face or surface of the mobile device 376. Ofcourse, in other embodiments, any number of other buttons, externalinputs/outputs, or digital inputs/outputs may be included on the mobiledevice 376, and which may be used in conjunction with the camera module330.

As shown, in one embodiment, a touch entry display system comprisingdisplay unit 312 is disposed on the opposite side of mobile device 376from camera module 330. In certain embodiments, the mobile device 376includes a user-facing camera module 331 and may include a user-facingstrobe unit (not shown). Of course, in other embodiments, the mobiledevice 376 may include any number of user-facing camera modules orrear-facing camera modules, as well as any number of user-facing strobeunits or rear-facing strobe units.

In some embodiments, the digital camera 302 and the mobile device 376may each generate and store a synthetic image based on an image stacksampled by camera module 330. The image stack may include one or moreimages sampled under ambient lighting conditions, one or more imagessampled under strobe illumination from strobe unit 336, or a combinationthereof.

FIG. 3E illustrates camera module 330, in accordance with oneembodiment. As an option, the camera module 330 may be implemented inthe context of the details of any of the Figures disclosed herein. Ofcourse, however, the camera module 330 may be implemented in any desiredenvironment. Further, the aforementioned definitions may equally applyto the description below.

In one embodiment, the camera module 330 may be configured to controlstrobe unit 336 through strobe control signal 338. As shown, a lens 390is configured to focus optical scene information 352 onto image sensor332 to be sampled. In one embodiment, image sensor 332 advantageouslycontrols detailed timing of the strobe unit 336 though the strobecontrol signal 338 to reduce inter-sample time between an image sampledwith the strobe unit 336 enabled, and an image sampled with the strobeunit 336 disabled. For example, the image sensor 332 may enable thestrobe unit 336 to emit strobe illumination 350 less than onemicrosecond (or any desired length) after image sensor 332 completes anexposure time associated with sampling an ambient image and prior tosampling a strobe image.

In other embodiments, the strobe illumination 350 may be configuredbased on a desired one or more target points. For example, in oneembodiment, the strobe illumination 350 may light up an object in theforeground, and depending on the length of exposure time, may also lightup an object in the background of the image. In one embodiment, once thestrobe unit 336 is enabled, the image sensor 332 may then immediatelybegin exposing a strobe image. The image sensor 332 may thus be able todirectly control sampling operations, including enabling and disablingthe strobe unit 336 associated with generating an image stack, which maycomprise at least one image sampled with the strobe unit 336 disabled,and at least one image sampled with the strobe unit 336 either enabledor disabled. In one embodiment, data comprising the image stack sampledby the image sensor 332 is transmitted via interconnect 334 to a camerainterface unit 386 within processor complex 310. In some embodiments,the camera module 330 may include an image sensor controller (e.g.,controller 333 of FIG. 3G), which may be configured to generate thestrobe control signal 338 in conjunction with controlling operation ofthe image sensor 332.

FIG. 3F illustrates a camera module 330, in accordance with oneembodiment. As an option, the camera module 330 may be implemented inthe context of the details of any of the Figures disclosed herein. Ofcourse, however, the camera module 330 may be implemented in any desiredenvironment. Further, the aforementioned definitions may equally applyto the description below.

In one embodiment, the camera module 330 may be configured to sample animage based on state information for strobe unit 336. The stateinformation may include, without limitation, one or more strobeparameters (e.g. strobe intensity, strobe color, strobe time, etc.), fordirecting the strobe unit 336 to generate a specified intensity and/orcolor of the strobe illumination 350. In one embodiment, commands forconfiguring the state information associated with the strobe unit 336may be transmitted through a strobe control signal 338, which may bemonitored by the camera module 330 to detect when the strobe unit 336 isenabled. For example, in one embodiment, the camera module 330 maydetect when the strobe unit 336 is enabled or disabled within amicrosecond or less of the strobe unit 336 being enabled or disabled bythe strobe control signal 338. To sample an image requiring strobeillumination, a camera interface unit 386 may enable the strobe unit 336by sending an enable command through the strobe control signal 338. Inone embodiment, the camera interface unit 386 may be included as aninterface of input/output interfaces 384 in a processor subsystem 360 ofthe processor complex 310 of FIG. 3B. The enable command may comprise asignal level transition, a data packet, a register write, or any othertechnically feasible transmission of a command. The camera module 330may sense that the strobe unit 336 is enabled and then cause imagesensor 332 to sample one or more images requiring strobe illuminationwhile the strobe unit 336 is enabled. In such an implementation, theimage sensor 332 may be configured to wait for an enable signal destinedfor the strobe unit 336 as a trigger signal to begin sampling a newexposure.

In one embodiment, camera interface unit 386 may transmit exposureparameters and commands to camera module 330 through interconnect 334.In certain embodiments, the camera interface unit 386 may be configuredto directly control strobe unit 336 by transmitting control commands tothe strobe unit 336 through strobe control signal 338. By directlycontrolling both the camera module 330 and the strobe unit 336, thecamera interface unit 386 may cause the camera module 330 and the strobeunit 336 to perform their respective operations in precise timesynchronization. In one embodiment, precise time synchronization may beless than five hundred microseconds of event timing error. Additionally,event timing error may be a difference in time from an intended eventoccurrence to the time of a corresponding actual event occurrence.

In another embodiment, camera interface unit 386 may be configured toaccumulate statistics while receiving image data from camera module 330.In particular, the camera interface unit 386 may accumulate exposurestatistics for a given image while receiving image data for the imagethrough interconnect 334. Exposure statistics may include, withoutlimitation, one or more of an intensity histogram, a count ofover-exposed pixels, a count of under-exposed pixels, anintensity-weighted sum of pixel intensity, or any combination thereof.The camera interface unit 386 may present the exposure statistics asmemory-mapped storage locations within a physical or virtual addressspace defined by a processor, such as one or more of CPU cores 370,within processor complex 310. In one embodiment, exposure statisticsreside in storage circuits that are mapped into a memory-mapped registerspace, which may be accessed through the interconnect 334. In otherembodiments, the exposure statistics are transmitted in conjunction withtransmitting pixel data for a captured image. For example, the exposurestatistics for a given image may be transmitted as in-line data,following transmission of pixel intensity data for the captured image.Exposure statistics may be calculated, stored, or cached within thecamera interface unit 386. In other embodiments, an image sensorcontroller within camera module 330 may be configured to accumulate theexposure statistics and transmit the exposure statistics to processorcomplex 310, such as by way of camera interface unit 386. In oneembodiment, the exposure statistics are accumulated within the cameramodule 330 and transmitted to the camera interface unit 386, either inconjunction with transmitting image data to the camera interface unit386, or separately from transmitting image data.

In one embodiment, camera interface unit 386 may accumulate colorstatistics for estimating scene white-balance. Any technically feasiblecolor statistics may be accumulated for estimating white balance, suchas a sum of intensities for different color channels comprising red,green, and blue color channels. The sum of color channel intensities maythen be used to perform a white-balance color correction on anassociated image, according to a white-balance model such as agray-world white-balance model. In other embodiments, curve-fittingstatistics are accumulated for a linear or a quadratic curve fit usedfor implementing white-balance correction on an image. As with theexposure statistics, the color statistics may be presented asmemory-mapped storage locations within processor complex 310. In oneembodiment, the color statistics may be mapped in a memory-mappedregister space, which may be accessed through interconnect 334. In otherembodiments, the color statistics may be transmitted in conjunction withtransmitting pixel data for a captured image. For example, in oneembodiment, the color statistics for a given image may be transmitted asin-line data, following transmission of pixel intensity data for theimage. Color statistics may be calculated, stored, or cached within thecamera interface 386. In other embodiments, the image sensor controllerwithin camera module 330 may be configured to accumulate the colorstatistics and transmit the color statistics to processor complex 310,such as by way of camera interface unit 386. In one embodiment, thecolor statistics may be accumulated within the camera module 330 andtransmitted to the camera interface unit 386, either in conjunction withtransmitting image data to the camera interface unit 386, or separatelyfrom transmitting image data.

In one embodiment, camera interface unit 386 may accumulate spatialcolor statistics for performing color-matching between or among images,such as between or among an ambient image and one or more images sampledwith strobe illumination. As with the exposure statistics, the spatialcolor statistics may be presented as memory-mapped storage locationswithin processor complex 310. In one embodiment, the spatial colorstatistics are mapped in a memory-mapped register space. In anotherembodiment the camera module may be configured to accumulate the spatialcolor statistics, which may be accessed through interconnect 334. Inother embodiments, the color statistics may be transmitted inconjunction with transmitting pixel data for a captured image. Forexample, in one embodiment, the color statistics for a given image maybe transmitted as in-line data, following transmission of pixelintensity data for the image. Color statistics may be calculated,stored, or cached within the camera interface 386.

In one embodiment, camera module 330 may transmit strobe control signal338 to strobe unit 336, enabling the strobe unit 336 to generateillumination while the camera module 330 is sampling an image. Inanother embodiment, camera module 330 may sample an image illuminated bystrobe unit 336 upon receiving an indication signal from camerainterface unit 386 that the strobe unit 336 is enabled. In yet anotherembodiment, camera module 330 may sample an image illuminated by strobeunit 336 upon detecting strobe illumination within a photographic scenevia a rapid rise in scene illumination. In one embodiment, a rapid risein scene illumination may include at least a rate of increasingintensity consistent with that of enabling strobe unit 336. In still yetanother embodiment, camera module 330 may enable strobe unit 336 togenerate strobe illumination while sampling one image, and disable thestrobe unit 336 while sampling a different image.

FIG. 3G illustrates camera module 330, in accordance with oneembodiment. As an option, the camera module 330 may be implemented inthe context of the details of any of the Figures disclosed herein. Ofcourse, however, the camera module 330 may be implemented in any desiredenvironment. Further, the aforementioned definitions may equally applyto the description below.

In one embodiment, the camera module 330 may be in communication with anapplication processor 335. The camera module 330 is shown to includeimage sensor 332 in communication with a controller 333. Further, thecontroller 333 is shown to be in communication with the applicationprocessor 335.

In one embodiment, the application processor 335 may reside outside ofthe camera module 330. As shown, the lens 390 may be configured to focusoptical scene information to be sampled onto image sensor 332. Theoptical scene information sampled by the image sensor 332 may then becommunicated from the image sensor 332 to the controller 333 for atleast one of subsequent processing and communication to the applicationprocessor 335. In another embodiment, the controller 333 may controlstorage of the optical scene information sampled by the image sensor332, or storage of processed optical scene information.

In another embodiment, the controller 333 may enable a strobe unit toemit strobe illumination for a short time duration (e.g. less than tenmilliseconds) after image sensor 332 completes an exposure timeassociated with sampling an ambient image. Further, the controller 333may be configured to generate strobe control signal 338 in conjunctionwith controlling operation of the image sensor 332.

In one embodiment, the image sensor 332 may be a complementary metaloxide semiconductor (CMOS) sensor or a charge-coupled device (CCD)sensor. In another embodiment, the controller 333 and the image sensor332 may be packaged together as an integrated system, multi-chip module,multi-chip stack, or integrated circuit. In yet another embodiment, thecontroller 333 and the image sensor 332 may comprise discrete packages.In one embodiment, the controller 333 may provide circuitry forreceiving optical scene information from the image sensor 332,processing of the optical scene information, timing of variousfunctionalities, and signaling associated with the application processor335. Further, in another embodiment, the controller 333 may providecircuitry for control of one or more of exposure, shuttering, whitebalance, and gain adjustment. Processing of the optical sceneinformation by the circuitry of the controller 333 may include one ormore of gain application, amplification, and analog-to-digitalconversion. After processing the optical scene information, thecontroller 333 may transmit corresponding digital pixel data, such as tothe application processor 335.

In one embodiment, the application processor 335 may be implemented onprocessor complex 310 and at least one of volatile memory 318 and NVmemory 316, or any other memory device and/or system. The applicationprocessor 335 may be previously configured for processing of receivedoptical scene information or digital pixel data communicated from thecamera module 330 to the application processor 335.

FIG. 4 illustrates a network service system 400, in accordance with oneembodiment. As an option, the network service system 400 may beimplemented in the context of the details of any of the Figuresdisclosed herein. Of course, however, the network service system 400 maybe implemented in any desired environment. Further, the aforementioneddefinitions may equally apply to the description below.

In one embodiment, the network service system 400 may be configured toprovide network access to a device implementing a digital photographicsystem. As shown, network service system 400 includes a wireless mobiledevice 376, a wireless access point 472, a data network 474, a datacenter 480, and a data center 481. The wireless mobile device 376 maycommunicate with the wireless access point 472 via a digital radio link471 to send and receive digital data, including data associated withdigital images. The wireless mobile device 376 and the wireless accesspoint 472 may implement any technically feasible transmission techniquesfor transmitting digital data via digital radio link 471 withoutdeparting the scope and spirit of the present invention. In certainembodiments, one or more of data centers 480, 481 may be implementedusing virtual constructs so that each system and subsystem within agiven data center 480, 481 may comprise virtual machines configured toperform data processing and network data transmission tasks. In otherimplementations, one or more of data centers 480, 481 may be physicallydistributed over a plurality of physical sites.

The wireless mobile device 376 may comprise a smart phone configured toinclude a digital camera, a digital camera configured to includewireless network connectivity, a reality augmentation device, a laptopconfigured to include a digital camera and wireless networkconnectivity, or any other technically feasible computing deviceconfigured to include a digital photographic system and wireless networkconnectivity.

In various embodiments, the wireless access point 472 may be configuredto communicate with wireless mobile device 376 via the digital radiolink 471 and to communicate with the data network 474 via anytechnically feasible transmission media, such as any electrical,optical, or radio transmission media. For example, in one embodiment,wireless access point 472 may communicate with data network 474 throughan optical fiber coupled to the wireless access point 472 and to arouter system or a switch system within the data network 474. A networklink 475, such as a wide area network (WAN) link, may be configured totransmit data between the data network 474 and the data center 480.

In one embodiment, the data network 474 may include routers, switches,long-haul transmission systems, provisioning systems, authorizationsystems, and any technically feasible combination of communications andoperations subsystems configured to convey data between networkendpoints, such as between the wireless access point 472 and the datacenter 480. In one implementation scenario, wireless mobile device 376may comprise one of a plurality of wireless mobile devices configured tocommunicate with the data center 480 via one or more wireless accesspoints coupled to the data network 474.

Additionally, in various embodiments, the data center 480 may include,without limitation, a switch/router 482 and at least one data servicesystem 484. The switch/router 482 may be configured to forward datatraffic between and among a network link 475, and each data servicesystem 484. The switch/router 482 may implement any technically feasibletransmission techniques, such as Ethernet media layer transmission,layer 2 switching, layer 3 routing, and the like. The switch/router 482may comprise one or more individual systems configured to transmit databetween the data service systems 484 and the data network 474.

In one embodiment, the switch/router 482 may implement session-levelload balancing among a plurality of data service systems 484. Each dataservice system 484 may include at least one computation system 488 andmay also include one or more storage systems 486. Each computationsystem 488 may comprise one or more processing units, such as a centralprocessing unit, a graphics processing unit, or any combination thereof.A given data service system 484 may be implemented as a physical systemcomprising one or more physically distinct systems configured to operatetogether. Alternatively, a given data service system 484 may beimplemented as a virtual system comprising one or more virtual systemsexecuting on an arbitrary physical system. In certain scenarios, thedata network 474 may be configured to transmit data between the datacenter 480 and another data center 481, such as through a network link476.

In another embodiment, the network service system 400 may include anynetworked mobile devices configured to implement one or more embodimentsof the present invention. For example, in some embodiments, apeer-to-peer network, such as an ad-hoc wireless network, may beestablished between two different wireless mobile devices. In suchembodiments, digital image data may be transmitted between the twowireless mobile devices without having to send the digital image data toa data center 480.

FIG. 5 illustrates bilinear interpolation artifacts 500.

As shown, item 502 is the original image, generated using prior artlocal equalization techniques (CLAHE technique known in the art). Item504 emphasizes that the artifacts are found within emphasis 506, withthe actual border artifacts faintly shown along dotted line border 508.To more clearly emphasize such artifacts, mid-tones from the item 502were adjusted towards shadows (using levels adjustment). In this manner,the darker hues associated with the sky are shown. Emphasis 510A showsfaint vertical artifacts, and emphasis 510B shows horizontal artifacts,both of which may result from conventional image interpolationalgorithms, in particular bilinear interpolation algorithms, includingbilinear interpolation used in CLAHE.

FIG. 6 illustrates a network architecture 600, in accordance with onepossible embodiment. As shown, at least one network 602 is provided. Inthe context of the present network architecture 600, the network 602 maytake any form including, but not limited to a telecommunicationsnetwork, a local area network (LAN), a wireless network, a wide areanetwork (WAN) such as the Internet, peer-to-peer network, cable network,etc. While only one network is shown, it should be understood that twoor more similar or different networks 602 may be provided.

Coupled to the network 602 is a plurality of devices. For example, aserver computer 612 and an end user computer 608 may be coupled to thenetwork 602 for communication purposes. Such end user computer 608 mayinclude a desktop computer, lap-top computer, and/or any other type oflogic. Still yet, various other devices may be coupled to the network602 including a personal digital assistant (PDA) device 610, a mobilephone device 606, a television 604, a camera 614, etc.

FIG. 7 illustrates an exemplary system 700, in accordance with oneembodiment. As an option, the system 700 may be implemented in thecontext of any of the devices of the network architecture 600 of FIG. 6. Of course, the system 700 may be implemented in any desiredenvironment.

As shown, a system 700 is provided including at least one centralprocessor 702 which is connected to a communication bus 712. The system700 also includes main memory 704 [e.g. random access memory (RAM),etc.]. The system700 also includes a graphics processor 708 and adisplay 710.

The system 700 may also include a secondary storage 706. The secondarystorage 706 includes, for example, a hard disk drive and/or a removablestorage drive, representing a floppy disk drive, a magnetic tape drive,a compact disk drive, etc. The removable storage drive reads from and/orwrites to a removable storage unit in a well known manner.

Computer programs, or computer control logic algorithms, may be storedin the main memory 704, the secondary storage 706, and/or any othermemory, for that matter. Such computer programs, when executed, enablethe system 700 to perform various functions (as set forth above, forexample). Memory 704, storage 706 and/or any other storage are possibleexamples of non-transitory computer-readable media.

It is noted that the techniques described herein, in an aspect, areembodied in executable instructions stored in a computer readable mediumfor use by or in connection with an instruction execution machine,apparatus, or device, such as a computer-based or processor-containingmachine, apparatus, or device. It will be appreciated by those skilledin the art that for some embodiments, other types of computer readablemedia are included which may store data that is accessible by acomputer, such as magnetic cassettes, flash memory cards, digital videodisks, Bernoulli cartridges, random access memory (RAM), read-onlymemory (ROM), and the like.

As used here, a “computer-readable medium” includes one or more of anysuitable media for storing the executable instructions of a computerprogram such that the instruction execution machine, system, apparatus,or device may read (or fetch) the instructions from the computerreadable medium and execute the instructions for carrying out thedescribed methods. Suitable storage formats include one or more of anelectronic, magnetic, optical, and electromagnetic format. Anon-exhaustive list of conventional exemplary computer readable mediumincludes: a portable computer diskette; a RAM; a ROM; an erasableprogrammable read only memory (EPROM or flash memory); optical storagedevices, including a portable compact disc (CD), a portable digitalvideo disc (DVD), a high definition DVD (HD-DVDTM), a BLU-RAY disc; andthe like.

It should be understood that the arrangement of components illustratedin the Figures described are exemplary and that other arrangements arepossible. It should also be understood that the various systemcomponents (and means) defined by the claims, described below, andillustrated in the various block diagrams represent logical componentsin some systems configured according to the subject matter disclosedherein.

For example, one or more of these system components (and means) may berealized, in whole or in part, by at least some of the componentsillustrated in the arrangements illustrated in the described Figures. Inaddition, while at least one of these components are implemented atleast partially as an electronic hardware component, and thereforeconstitutes a machine, the other components may be implemented insoftware that when included in an execution environment constitutes amachine, hardware, or a combination of software and hardware.

More particularly, at least one component defined by the claims isimplemented at least partially as an electronic hardware component, suchas an instruction execution machine (e.g., a processor-based orprocessor-containing machine) and/or as specialized circuits orcircuitry (e.g., discreet logic gates interconnected to perform aspecialized function). Other components may be implemented in software,hardware, or a combination of software and hardware. Moreover, some orall of these other components may be combined, some may be omittedaltogether, and additional components may be added while still achievingthe functionality described herein. Thus, the subject matter describedherein may be embodied in many different variations, and all suchvariations are contemplated to be within the scope of what is claimed.

In the description above, the subject matter is described with referenceto acts and symbolic representations of operations that are performed byone or more devices, unless indicated otherwise. As such, it will beunderstood that such acts and operations, which are at times referred toas being computer-executed, include the manipulation by the processor ofdata in a structured form. This manipulation transforms the data ormaintains it at locations in the memory system of the computer, whichreconfigures or otherwise alters the operation of the device in a mannerwell understood by those skilled in the art. The data is maintained atphysical locations of the memory as data structures that have particularproperties defined by the format of the data. However, while the subjectmatter is being described in the foregoing context, it is not meant tobe limiting as those of skill in the art will appreciate that various ofthe acts and operations described hereinafter may also be implemented inhardware.

To facilitate an understanding of the subject matter described herein,many aspects are described in terms of sequences of actions. At leastone of these aspects defined by the claims is performed by an electronichardware component. For example, it will be recognized that the variousactions may be performed by specialized circuits or circuitry, byprogram instructions being executed by one or more processors, or by acombination of both. The description herein of any sequence of actionsis not intended to imply that the specific order described forperforming that sequence must be followed. All methods described hereinmay be performed in any suitable order unless otherwise indicated hereinor otherwise clearly contradicted by context.

The use of the terms “a” and “an” and “the” and similar referents in thecontext of describing the subject matter (particularly in the context ofthe following claims) are to be construed to cover both the singular andthe plural, unless otherwise indicated herein or clearly contradicted bycontext. Recitation of ranges of values herein are merely intended toserve as a shorthand method of referring individually to each separatevalue falling within the range, unless otherwise indicated herein, andeach separate value is incorporated into the specification as if it wereindividually recited herein. Furthermore, the foregoing description isfor the purpose of illustration only, and not for the purpose oflimitation, as the scope of protection sought is defined by the claimsas set forth hereinafter together with any equivalents thereof entitledto. The use of any and all examples, or exemplary language (e.g., “suchas”) provided herein, is intended merely to better illustrate thesubject matter and does not pose a limitation on the scope of thesubject matter unless otherwise claimed. The use of the term “based on”and other like phrases indicating a condition for bringing about aresult, both in the claims and in the written description, is notintended to foreclose any other conditions that bring about that result.No language in the specification should be construed as indicating anynon-claimed element as essential to the practice of the invention asclaimed.

The embodiments described herein included the one or more modes known tothe inventor for carrying out the claimed subject matter. Of course,variations of those embodiments will become apparent to those ofordinary skill in the art upon reading the foregoing description. Theinventor expects skilled artisans to employ such variations asappropriate, and the inventor intends for the claimed subject matter tobe practiced otherwise than as specifically described herein.Accordingly, this claimed subject matter includes all modifications andequivalents of the subject matter recited in the claims appended heretoas permitted by applicable law. Moreover, any combination of theabove-described elements in all possible variations thereof isencompassed unless otherwise indicated herein or otherwise clearlycontradicted by context.

What is claimed is:
 1. A device, comprising: a non-transitory memorystoring instructions; and one or more processors in communication withthe non-transitory memory, wherein the one or more processors executethe instructions to: compute a first cumulative distribution functionfor a first histogram of a first pixel region of a first image, whereinthe first pixel region is based on a first vertical distance, a secondvertical distance, a first horizontal distance, and a second horizontaldistance based on a first pixel of the first image; extract a first setof parameters for the first cumulative distribution function; compute asecond cumulative distribution function for a second histogram of asecond pixel region of the first image, wherein the second pixel regionis based on a third vertical distance, a fourth vertical distance, athird horizontal distance, and a fourth horizontal distance based on asecond pixel of the first image; extract a second set of parameters forthe second cumulative distribution function; and create an interpolatedcumulative distribution function comprising interpolated parameterscalculated by interpolating between the first set of parameters and thesecond set of parameters; and generate a first equalized pixel in asecond image based on the interpolated cumulative distribution function.2. The device of claim 1, wherein the first set of parameters and thesecond set of parameters each comprise control points.
 3. The device ofclaim 2, wherein the first set of parameters and the second set ofparameters further comprise an angle for each control point of thecontrol points.
 4. The device of claim 1, wherein the interpolatedcumulative distribution function comprises a Bezier curve comprisinginterpolated control points and interpolated angles.
 5. The device ofclaim 1, wherein the interpolated cumulative distribution functioncomprises a spline curve comprising interpolated control points.
 6. Thedevice of claim 1, wherein the interpolated parameters for theinterpolated cumulative distribution function are weighted according toa position of the first input pixel.
 7. The device of claim 6, whereinthe weighted interpolated parameters are applied horizontally.
 8. Thedevice of claim 6, wherein the weighted interpolated parameters areapplied vertically.
 9. The device of claim 1, wherein during a firstprocessing pass on the first image, the one or more processors executethe instructions to generate and store parameters, including the firstand second sets of parameters, for at least the first pixel region ofthe first image and the second pixel region of the first image.
 10. Thedevice of claim 9, wherein the parameters are stored in a texture map.11. The device of claim 1, wherein the interpolating comprises bicubicinterpolation.
 12. The device of claim 1, wherein the device is operablesuch that a first portion of pixel regions of the first image isselected based on a pixel of interest.
 13. The device of claim 12,wherein the device is operable such that the pixel of interest isassociated with an identified object.
 14. The device of claim 13,wherein the device is operable such that a priority associated with theidentified object is predetermined.
 15. A method, comprising: computing,using a processor, a first cumulative distribution function for a firsthistogram of a first pixel region of a first image, wherein the firstpixel region is based on a first vertical distance, a second verticaldistance, a first horizontal distance, and a second horizontal distancebased on a first pixel of the first image; extracting, using theprocessor, a first set of parameters for the first cumulativedistribution function; computing, using the processor, a secondcumulative distribution function for a second histogram of a secondpixel region of the first image, wherein the second pixel region isbased on a third vertical distance, a fourth vertical distance, a thirdhorizontal distance, and a fourth horizontal distance based on a secondpixel of the first image; extracting, using the processor, a second setof parameters for the second cumulative distribution function; creating,using the processor, an interpolated cumulative distribution functioncomprising interpolated parameters calculated by interpolating betweenthe first set of parameters and the second set of parameters; andgenerating, using the processor, a first equalized pixel in a secondimage based on the interpolated cumulative distribution function.
 16. Acomputer program product comprising computer executable instructionsstored on a non-transitory computer readable medium that when executedby a processor instruct the processor to: compute a first cumulativedistribution function for a first histogram of a first pixel region of afirst image, wherein the first pixel region is based on a first verticaldistance, a second vertical distance, a first horizontal distance, and asecond horizontal distance based on a first pixel of the first image;extract a first set of parameters for the first cumulative distributionfunction; compute a second cumulative distribution function for a secondhistogram of a second pixel region of the first image, wherein thesecond pixel region is based on a third vertical distance, a fourthvertical distance, a third horizontal distance, and a fourth horizontaldistance based on a second pixel of the first image; extract a secondset of parameters for the second cumulative distribution function;create an interpolated cumulative distribution function comprisinginterpolated parameters calculated by interpolating between the firstset of parameters and the second set of parameters; and generate a firstequalized pixel in a second image based on the interpolated cumulativedistribution function.